#1
pirates <- read.table("http://nathanieldphillips.com/wp-content/uploads/2015/05/pirate_survey_noerrors.txt", sep = "\t", header = T, stringsAsFactors = F)
data <- c(1, -5, 2, 3, 2, 1, 3, 4)
result <- t.test(data)
result
##
## One Sample t-test
##
## data: data
## t = 1.4019, df = 7, p-value = 0.2037
## alternative hypothesis: true mean is not equal to 0
## 95 percent confidence interval:
## -0.9443258 3.6943258
## sample estimates:
## mean of x
## 1.375
head(pirates)
## id sex headband age college tattoos tchests.found parrots.lifetime
## 1 1 female yes 35 JSSFP 18 8 9
## 2 2 male yes 21 CCCC 6 5 1
## 3 3 female yes 27 CCCC 12 8 1
## 4 4 male yes 19 CCCC 9 8 1
## 5 5 male yes 31 CCCC 11 2 13
## 6 6 male yes 21 CCCC 7 1 0
## favorite.pirate sword.type sword.speed
## 1 Blackbeard cutlass 0.0638977084
## 2 Blackbeard cutlass 0.5601675763
## 3 Anicetus cutlass 0.0005400172
## 4 Jack Sparrow cutlass 3.8770396912
## 5 Jack Sparrow cutlass 0.5080594239
## 6 Jack Sparrow cutlass 0.6248019344
#2
t.test ( x=pirates$age, mu=25, alternative= "g")
##
## One Sample t-test
##
## data: pirates$age
## t = 14.5068, df = 999, p-value < 2.2e-16
## alternative hypothesis: true mean is greater than 25
## 95 percent confidence interval:
## 27.34393 Inf
## sample estimates:
## mean of x
## 27.644
#Conclusion: t(999)=14.507, p <0.001 , 95% CI = [27.34, Inf]
#3
t.test (x=pirates$parrots.lifetime, mu= 2.7, alternative = "g")
##
## One Sample t-test
##
## data: pirates$parrots.lifetime
## t = 0.7298, df = 999, p-value = 0.2329
## alternative hypothesis: true mean is greater than 2.7
## 95 percent confidence interval:
## 2.615845 Inf
## sample estimates:
## mean of x
## 2.767
#Conclusion: t(999)=0.729, p = 0.2329 , 95% CI [2.615, Inf]
#4
swordspeed.cccc <- subset(pirates, subset = college == "CCCC")$sword.speed
swordspeed.jssfp <- subset(pirates, subset = college == "JSSFP")$sword.speed
test.result <- t.test (x = swordspeed.cccc,
y = swordspeed.jssfp,
alternative = "l")
test.result
##
## Welch Two Sample t-test
##
## data: swordspeed.cccc and swordspeed.jssfp
## t = -1.4524, df = 540.345, p-value = 0.07348
## alternative hypothesis: true difference in means is less than 0
## 95 percent confidence interval:
## -Inf 0.03610759
## sample estimates:
## mean of x mean of y
## 1.068027 1.336603
#Conclusion: t(540.345)=-1.4524, p = 0.07348 , 95% CI [-Inf, 0.036]
#5
favoritepirate.blackbeard <- subset(pirates, subset = favorite.pirate =="Blackbeard")$tattoos
favoritepirate.jacksparrow<- subset(pirates, subset = favorite.pirate =="Jack Sparrow")$tattoos
test.result <- t.test (x = favoritepirate.blackbeard,
y = favoritepirate.jacksparrow,
alternative = "l")
test.result
##
## Welch Two Sample t-test
##
## data: favoritepirate.blackbeard and favoritepirate.jacksparrow
## t = 0.0333, df = 137.3, p-value = 0.5133
## alternative hypothesis: true difference in means is less than 0
## 95 percent confidence interval:
## -Inf 0.6561283
## sample estimates:
## mean of x mean of y
## 9.620000 9.607064
test.result <- t.test (formula= tattoos ~ favorite.pirate,
subset = favorite.pirate %in% c("Jack Sparrow", "Blackbeard"),
data = pirates,
alternative = "l")
test.result
##
## Welch Two Sample t-test
##
## data: tattoos by favorite.pirate
## t = 0.0333, df = 137.3, p-value = 0.5133
## alternative hypothesis: true difference in means is less than 0
## 95 percent confidence interval:
## -Inf 0.6561283
## sample estimates:
## mean in group Blackbeard mean in group Jack Sparrow
## 9.620000 9.607064
#Conclusion: t(137.3)= 0.0333, p = 0.5133 , 95% CI [-Inf, 0.6561283]
#6
test.result <- cor.test (x = pirates$age,
y = pirates$tchests.found)
test.result
##
## Pearson's product-moment correlation
##
## data: pirates$age and pirates$tchests.found
## t = 2.8263, df = 998, p-value = 0.004802
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.02726784 0.15027323
## sample estimates:
## cor
## 0.08911029
#Conclusion: t(998)= 2.8263, p = 0.004802 , 95% CI [0.027, 0.0150]
#7
lessthanten <- subset(pirates, subset =parrots.lifetime < 10)
favoritepirate.jacksparrow <- subset(pirates, subset = favorite.pirate =="Jack Sparrow")
test.result2 <- cor.test (formula = ~ age + tchests.found,
subset = favorite.pirate %in% c("Jack Sparrow") & parrots.lifetime < 10,
data=pirates,
alternative = "two.sided")
test.result2
##
## Pearson's product-moment correlation
##
## data: age and tchests.found
## t = 1.88, df = 437, p-value = 0.06077
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.004053305 0.181639084
## sample estimates:
## cor
## 0.08957122
#Conclusion: t(437)= 1.88, p = 0.06077 , 95% CI [0.004, 0.181]
#8
test.result <- with(pirates, chisq.test(x=college, y=favorite.pirate))
test.result
##
## Pearson's Chi-squared test
##
## data: college and favorite.pirate
## X-squared = 44.5956, df = 5, p-value = 1.753e-08
#Conclusion: X-squared(5)= 44.5956, p < 0.001